Content management systems can help users and administrators to classify data so that intelligible and relevant information may be returned to a specific type of user. For example, a worldwide email system might be able to access resources from many different countries and in many different languages. A user, however, may not need different language versions of the same content or versions of the same content adapted for different cultures. By localizing the content for a particular user or type of user, it is possible to greatly reduce the universe of information to be presented to the user. Localizing content for a user may be thought of as either gathering desirable information elements together from an undesirably large universe of information, or conversely, filtering out undesirable information elements from a pre-existing set of desirable information elements.
FIG. 1 shows a conventional manner of localizing resources for a user or application. Within an information universe 100, a common attribute is applied in a filtering process to localize a target environment for a user that is made up of a localized subset 102 of information resources that have the common attribute. A user query 104, for example, can then operate within those information resources in the localized subset 102 that comprise the user's environment.
In the context of an application that has access to information resources on a worldwide scale, one attribute for creating a localized subset 102 of information resources is language. Another attribute for creating a localized subset 102 of information resources is the associated country or geopolitical setting of a user or a resource. These two attributes, language and country, are conventionally used for localizing information resources, but provide only a rough localization, even when combined.
FIG. 2 shows a conventional database 200 for arranging attributes used to localize information resources. The conventional database 200 is typically represented by a table having a first attribute column 202 and a second attribute column 204. The first attribute column 202 is typically reserved for the localizing attribute, “language” 206. Fields for “language” values, such as English 210 and Spanish 212 are provided. The second attribute column 204 is typically reserved for the localizing attribute, “country” 208. Fields for “country” values, such as Canada 214 and Mexico 216 are provided. In a typical conventional content management system, the conventional database 200 has capacity for only the two attributes, and applications using the conventional database 200 are often dependent on this conventional database structure.
As shown in FIG. 3, a localization of resources by adding a language attribute value, such as “Spanish” 212, to a country attribute value, such as Mexico 216 results in a localization to only those “Spanish” and “Mexico” resources 302 in the intersection of sets wherein a resource has both an attribute of “Spanish” 212 and an attribute of “Mexico” 216. Such a localization is an improvement over the non-localized entire universe of information resources 100, but is still not very specific.
Returning to FIG. 2, to add a third, new attribute 218 for further localizing resources beyond “Spanish” 212 and “Mexico” 216 attributes would require changing the structure of the conventional database 200 to add a third attribute column 220 reserved for the new attribute 218 and new fields for the new attribute values 222, 224. Not only is this difficult to implement if applications are dependent on the structure of the conventional database 200, but the structure of the conventional database 200 would have to be changed every time an attribute is added or subtracted from the structure. Further, using multiple attributes is conventionally avoided because numerous attributes increase the chance for an inaccurate localization as some attributes of lesser importance may be overrepresented compared to others that should be primary determinants of localization results.